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Alopecia Areata Is Associated with Atopic Diathesis: Results from a Population-Based Study of 51,561 Patients
Journal Pre-proof Alopecia Areata is Associated with Atopic Diathesis; Results from a Population-Based Study of 51,561 Patients Khalaf Kridin, MD, PhD, Yael Renert-Yuval, MD, Emma Guttman-Yassky, MD, PhD, Arnon D. Cohen, MD, MPH, PhD PII:
S2213-2198(20)30139-2
DOI:
https://doi.org/10.1016/j.jaip.2020.01.052
Reference:
JAIP 2682
To appear in:
The Journal of Allergy and Clinical Immunology: In Practice
Received Date: 24 October 2019 Revised Date:
3 January 2020
Accepted Date: 8 January 2020
Please cite this article as: Kridin K, Renert-Yuval Y, Guttman-Yassky E, Cohen AD, Alopecia Areata is Associated with Atopic Diathesis; Results from a Population-Based Study of 51,561 Patients The Journal of Allergy and Clinical Immunology: In Practice (2020), doi: https://doi.org/10.1016/ j.jaip.2020.01.052. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier Inc. on behalf of the American Academy of Allergy, Asthma & Immunology
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Title: Alopecia Areata is Associated with Atopic Diathesis;
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Results from a Population-Based Study of 51,561 Patients
3 4
Khalaf Kridin, MD, PhD,1*¶ Yael Renert-Yuval, MD,2* Emma Guttman-Yassky, MD, PhD,3**
5
Arnon D Cohen, MD, MPH, PhD4**
6 7
1
Department of Dermatology, Rambam Health Care Campus, Haifa, Israel
8
2
Laboratory for Investigative Dermatology, Rockefeller University, New York, NY, USA
9
3
Department of Dermatology and the Laboratory for Inflammatory Skin Diseases, Icahn School
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of Medicine at Mount Sinai, New York, NY, USA
11
4
12
Gurion University of the Negev, Beer-Sheva, Israel
Siaal Research Center for Family Medicine and Primary Care, Faculty of Health Sciences, Ben-
13 14
* - Equal contribution, ** - Equal contribution
15 16
¶
17
Khalaf Kridin, MD, PhD
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Department of Dermatology
19
Rambam Health Care Campus
20
POB 9602
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Haifa 31096, Israel
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Email: [email protected]
23
Telephone:+ 972-526506441
Corresponding Author:
1
24
Word count: 2208
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Tables: 5
26
Funding: This research did not receive any specific grant from funding agencies in the public,
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commercial, or not-for-profit sectors.
28
Conflict of interest: EGY is an employee of Mount Sinai and has received research funds
29
(grants paid to the institution) from Abbvie, Asana Biosciences, Celgene, Dermavant, DS
30
Biopharma, Galderma, Glenmark, Innovaderm, Janssen Biotech, Leo Pharma, Novan, Novartis,
31
Pfizer, Ralexar, Regeneron, and Union Therapeutics. EGY is also a consultant for Abbvie,
32
Allergan, Amgen, Asana Biosciences, Celgene, Concert, DBV Technologies, Dermira, DS
33
Biopharma, Eli Lilly, EMD Serono, Escalier, Flx Bio, Galderma, Glenmark, Kyowa Kirin, Leo
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Pharma, Mitsubishi Tanabe, Novartis, Pfizer, Regeneron, Sanofi, and Union Therapeutics. ADC
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received research grants from Janssen, Novartis and AbbVie, and served as a consultant, advisor
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or speaker to AbbVie, Amgen, Boehringer Ingelheim, Dexcel pharma, Janssen, Lilly, Neopharm,
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Novartis, Perrigo, Pfizer and Rafa. Other authors have declared that they have no conflict of
38
interest.
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2
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Abstract
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Background: Evidence of Th1/interferon (IFN)γ over-activation as major pathogenic driver
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somewhat conflicts with data supporting robust allergic background in alopecia areata (AA)
45
patients. Previous investigations of immunologic dysregulations show both Th1 and Th2-
46
related markers are over-expressed in AA. Clinical correlations in large populations may shed
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light on the immune pathways most likely to result in the clinical phenotype of AA.
48
Objective: To investigate the atopic comorbidities among patients with AA in a large,
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population-based study.
50
Methods: This is a cross-sectional retrospective study of AA patients and a matched
51
comparison group, analyzing the associations between AA and four atopic comorbidities:
52
asthma, atopic dermatitis (AD), allergic rhinitis, and allergic conjunctivitis. Chi-square and t-
53
tests were used for univariate analysis, and logistic regression model was used for
54
multivariate analysis. The study was performed utilizing the computerized database of Clalit
55
Health Services ensuring 4.4 million subjects.
56
Results: The study population includes 51,561 AA patients and 51,410 matched control
57
subjects. The prevalence of asthma (7.8% vs. 6.5%; OR 1.22; 95%CI 1.17-1.28, p<0.001),
58
AD (3.9% vs. 2.6%; OR 1.55; 95%CI 1.44-1.66, p<0.001), allergic rhinitis (16.0% vs. 12.8%;
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OR 1.29; 95%CI 1.25-1.34, p<0.001), and allergic conjunctivitis (23.5% vs. 19.6%; OR 1.27;
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95%CI 1.23-1.30, p <0.001) was significantly higher among patients with AA as compared to
61
matched control subjects. AA patients also had significantly higher probability to have more
62
than one atopic comorbidity, with increasing OR as the number of concomitant atopic
63
conditions increases.
3
64
Conclusion: Our analysis supports the previous literature and provides strong generalizability
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of significant atopy in AA patients, suggesting Th2 pathogenicity in AA, and challenging the
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traditional view of AA as a single axis, Th1-centered disease.
67
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68 69 70 71 72 73 74 75 76 77
Highlights box - no longer than 35 words in each • • •
What is already known about this topic? There is conflicting evidence for both Th1/interferon (IFN)γ and Th2-related markers as drivers of the inflammatory process of alopecia areata (AA). What is already known about this topic? AA patients had significant atopic associations as compared to a matched control group, in line with previous, smaller-scale publications. These findings lend weight to the concept of Th2-skewing in AA. What is already known about this topic? Our study reinforces a rationale for Th2targeting approaches in patients with AA.
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Key words: Alopecia areata, population based, atopic dermatitis, asthma, allergic rhinitis,
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allergic conjunctivitis, comorbidities, atopy, big data.
80 81
Abbreviations used:
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AA: Alopecia areata
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AD: Atopic dermatitis
84
CHS: Clalit Health Services
85
CI: Confidence interval
86
OR: Odds ratio
87
5
88
Introduction
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Alopecia areata (AA) is a common dermatologic disease, affecting up to 2% of the population,
90
and is characterized by non-scarring hair loss.1-3 Clinical presentations range from patchy,
91
circumscribed hair loss to alopecia totalis or universalis (complete loss of scalp hair or scalp and
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body hair, respectively).3 Despite significant emotional and psychosocial distress for patients and
93
their families,4 AA has no definitive, safe, and effective treatment,5-8 and the incomplete
94
understanding of AA pathogenesis hinders further therapeutic developments.9,10 While consensus
95
exists for the hair follicle immune privilege disruption as a trigger of hair follicle immune
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attack,11 the immune pathways driving the inflammatory response resulting in hair loss are not
97
yet fully elucidated. Traditionally, Th1/interferon/IFNγ-related cytokines and chemokines have
98
been viewed as chief players in AA initiation and maintenance, as supported by animal
99
models.12,13 The newly introduced Janus kinase/JAK inhibitors were also shown to downregulate
100
Th1/IFNγ and associated markers, along with other immune axes, such as Th2 coupled with up-
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regulations of hair keratins.14-16 Moreover, dysregulations of Th1/IFNγ, Th2, IL-9, PDE4, and
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Th17/IL-23 were found in several human and in mouse AA studies.12,17,18 Increasing evidence
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for a possible role of Th2 immune pathway in AA is supported by the high levels of Th2- related
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cytokines (e.g. IL-4, IL-5, IL-10) in skin and serum of AA patients, as well as findings of
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eosinophilia and elevated IgE levels in blood from AA patients.17,19-21 Moreover, genetic studies
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have identified polymorphisms in filaggrin, IL-4, and IL-13 (key players of the Th2 pathway) in
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AA patients, and associated filaggrin mutations with AA severity.19,22,23
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Few preliminary epidemiological studies and meta-analyses have shown a higher
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prevalence of atopic diseases, such as atopic dermatitis (AD), asthma, and allergic rhinitis
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(commonly driven by Th2-skewing) in patients with AA, hinting towards a shared
6
111
immunological background in these conditions.3,24-28 Last, the therapeutic armamentarium
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available for patients with atopic conditions, including AD, is rapidly expanding,29 and it is thus
113
important to further understand the associations between these conditions and AA.
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We investigated the association between AA and Th2-related diseases in a uniquely large
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and detailed database from Israel, in which patients have long-term follow-up of various health-
116
related systems. We opted to complement previous data suggesting Th2 skewing in AA patients.
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To the best of our knowledge, this is the largest population-based study investigating the atopic
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comorbidities of AA patients, encompassing more than 4.4 million patients.
119 120
Methods
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Study design and setting
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The current study was designed as a cross-sectional retrospective study utilizing
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information from the Clalit Health Services (CHS) database. CHS is the largest health
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maintenance organization in Israel, serving a population of approximately 4,400,000 as for 2017.
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CHS has a comprehensive computerized database with incessant real-time input from medical,
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administrative, and pharmaceutical computerized operating systems that enables data collection
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for epidemiological studies. The validity of diagnoses in this dataset, which are based on reports
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from both hospital and primary care physicians and specialists, was proven highly reliabile9. A
129
chronic disease register is gathered from these data sources and continuously updated and
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validated through algorithmic checks9. The current study was approved by the institutional
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ethical board of Ben-Gurion University and CHS.
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Study population and covariates
7
133
All medical records of CHS enrollees were screened for the diagnosis of AA, and data on
134
prevalent cases of AA was retrieved. The diagnosis of AA was based on the documentation of an
135
AA-specific diagnostic code registered by a board-certified dermatologist. A comparison group
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of individuals without AA was selected through 1:1 matching based on age, sex, ethnicity, and
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primary care practice. The control group was randomly selected from the list of CHS enrollees'
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frequency-matched to cases, excluding case patients with AA. Age matching was grounded on
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the exact year of birth (1-year strata).
140
Other covariates in the analysis included: comorbid conditions as determined using
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Charlson comorbidity index,10 a weighted index used to categorize the degree of comorbidity of
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a patient by taking into account the number and seriousness of comorbid conditions. This
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validated method has been shown to be a robust predictor of mortality and it correlates positively
144
with a fatal outcome.10 Socioeconomic status was defined according to the poverty index of the
145
patient's residence area as defined during the 2008 National Census. The population was divided
146
into 3 categories according to their poverty index (low, intermediate, and high)11. Data on
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ethnicity was based on the address of the patient’s primary care clinic. The vast majority of the
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Arab population in Israel resides in highly homogenous Arab towns and villages. Patients
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affiliated to healthcare facilities in these towns are designated as belonging to the “Arab Sector”.
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Thus, primary care clinic location represents a relatively precise measure of the ethnicity of
151
patients in Israel.
152
Statistical analysis
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The distribution of sociodemographic and clinical features was compared between case
154
and control subjects using chi-square test for sex and socioeconomic status, and t-test for age.
155
Conditional logistic regression was then used to calculate adjusted odds ratio (OR), and 95%
8
156
confidence interval (CI), to compare cases and controls with respect to the presence of atopic
157
comorbidities. All statistical analyses were performed using SPSS software, version 23 (SPSS,
158
Chicago, IL, USA).
159 160
Results
161
Our study population comprised of 51,561 patients with AA and 51,410 age- and sex-
162
matched control subjects. The mean age (±standard deviation/SD) of patients with AA was
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34.1±17.1, which is identical to that of control subjects at the date of enrollment. Overall, 20,476
164
(39.7%) of AA patients were females and a similar proportion was documented among controls.
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No significant differences in ethnic background and socioeconomic status were noted between
166
the two groups. Comorbidity rates, measured by the Charlson comorbidity index, were
167
comparable between the two groups, with 1,352 (2.6%) AA patients and 1,354 (2.6%) control
168
subjects experiencing severe comorbidities. The mean body mass index (BMI) was lower among
169
patients with AA (Table 1).
170
We evaluated the presence of four atopic conditions (AD, asthma, allergic rhinitis, and
171
allergic conjunctivitis) among AA patients and control groups. Table 2 demonstrates the
172
proportions of AA patients and controls with atopic comorbidities stratified by sex and age
173
category. The prevalence of asthma (7.8% vs. 6.5%; p<0.001), AD (3.9% vs. 2.6%; p<0.001),
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allergic rhinitis (16.0% vs. 12.8%; p<0.001), and allergic conjunctivitis (23.5% vs. 19.6%;
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p<0.001) was significantly higher among patients with AA as compared to matched control
176
subjects. In both AA and controls, the highest prevalence of both AD and Allergic conjunctivitis
177
was reported in patients younger than 20 years of age. Table 3 presents the results of univariate
178
and logistic regression models, and summarizes ORs for atopic conditions in patients with AA
9
179
and controls across the entire study sample. Among included atopic diseases, AD demonstrated
180
the strongest association with AA (OR, 1.55; 95% CI, 1.44-1.66). A milder, but still statistically
181
significant increase, was observed in the odds of asthma (OR, 1.22; 95% CI, 1.17–1.28), allergic
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rhinitis (OR, 1.29; 95% CI, 1.25–1.34), and allerigc conjuncitivits (OR, 1.27; 95% CI, 1.23–
183
1.30) among patients with AA relative to control subjects. In a multivariate logistic regression
184
model, adjustment for age, sex, ethnicity, socioeconomic status, and comorbidities did not
185
interfere with any of the aforementioned significant associations (Table 3).
186
We compared the characteristics of patients with AA presenting with comorbid atopic
187
diseases relative to patients with isolated AA (Table 4). Patients with comorbid asthma and AD
188
presented with their AA at a significantly earlier age, whereas patients with comorbid allergic
189
rhinitis developed AA at an older age. An overwhelming male preponderance was observed
190
among patients with AA and comorbid allergic rhinitis, whereas a slighter female predominance
191
emerged among patients with AA and comorbid AD and allergic conjunctivitis. Notably, patients
192
with AA and comorbid allergic rhinitis, AD and, to a lesser extent, allergic conjunctivitis were
193
less frequently exposed to cigarette smoking (Table 4).
194
Lastly, we investigated the association between having one or more atopic comorbidities
195
in AA patients as compared to controls. The prevalence of at least a single atopic comorbidity
196
was greater among patients with AA as compared to control subjects (39.5% vs. 32.9%,
197
respectively; OR, 1.33; 95% CI, 1.30–1.37; p<0.001). The prevalence of two or more (≥2)
198
concomitant atopic conditions was significantly higher among AA patients than controls (10.1%
199
vs. 7.5%, respectively; OR, 1.39; 95% CI, 1.34–1.46; p<0.001). When the probability of having
200
three or more (≥3) concomitant atopic conditions was compared, even a more robust association
201
was revealed (1.5% vs. 1.0%, respectively; OR, 1.54; 95% CI, 1.37–1.72; p<0.001). All the
10
202
aforementioned associations were robust to a multivariate analysis adjusting for age, sex,
203
ethnicity, socioeconomic status, and comorbidities (Table 5).
204 205 206
Discussion
207
Various comorbidities been reported in patients with AA, including psychological,
208
autoimmune, and atopic diseases.24-26,30,31 However, the association between AA and atopic
209
diseases has been evaluated in small cohorts.24-28 In the current population-based study, we
210
investigated the prevalence of atopic comorbidities in 51,561 patients with AA and 51,410
211
matched controls, to better characterize these associations. Of all four atopic comorbidities
212
included in this study, the most robust association of AA was with concomitant AD. The most
213
prevalent atopic disease in the entire cohort was allergic conjunctivitis, similar to previous
214
publications,32 and AA was also significantly associated with this condition, although to a lesser
215
extent in comparison with.
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AA patients with concomitant AD and asthma were associated with an earlier onset of
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AA, similar to prior reports.25,26 This together with the fact that early AA onset is recognized as a
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risk factor for more recalcitrant disease,33 potentially support a shared underlying immune
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dysregulation in the disease burden of AA and the atopic comorbidities. Notably, significanly
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more AA patients with concomitant AD, allergic rhinitis, and allergic conjuctivitis were non-
221
smokers, theoratically hinting towards an anti-inflammatory, nicotine-mediated effect, as seen in
222
ulcerative colitis and pemphigus.34,35 Despite these findings, because the overall hazards of
223
smoking are well known, and lung cancer-related mortatility is particularly higher in AA
224
patients,36 smoking cessation recommendations should still be stressed in AA patients.
11
225
Since atopic diseases are often manifested concomitantly, a phenomenon referred to as
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the “atopic march” in the pediatric population,37 we evaluated the OR of patients with AA to
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have several atopic comorbidities in comparison to patients without AA. We found that patients
228
with AA are more likely to suffer from concomitant atopic comorbidities with increasing OR as
229
the number of concomitant atopic conditions increases.
230
The mechanisms leading to the clinical manifestations of AA are still elusive, although
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recent research efforts portray an immune-mediated disease with variable activation of polar
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cytokine axes, including both Th1 and Th2.17 Th2 upregulations can be anticipated in patients
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with concomitant atopic diseases, specifically AD, asthma, and allergic rhinitis patients, in which
234
Th2 pathway pathogenicity has been recently demonstrated by the efficacy of Th2-targeting
235
agents.38-40 Of note, a large study evaluating scalp of AA patients with and without AD, did not
236
show differences in Th2 activation in AA patients, regardless of their atopic status.17
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Furthermore, in a large genome-wide association study, IL-13 has been the strongest association
238
in AA patients, regardless of concomitant AD.22 The atopic associations in AA patients have led
239
to testing of anti-histamines with beneficial effects in some AA patients, leading to several
240
reports advocating for concomitant antihistamine use together with other treatments in AA
241
patients.41-43
242
AA management presents significant unmet needs, particularly in patients with moderate
243
to severe hair loss, where intra-lesional and conventional therapeutics have limited applicability
244
and efficacy.9,10,44 Due to significant associations between atopic diseases and AA, as well as the
245
increasing evidence of up-regulations of Th2-related products in AA skin and blood,17,19-21,45,46 a
246
rationale for possible anti-Th2 approaches emerges in AA patients. This is also supported by few
247
case reports of significant hair regrowth in AA patients with totalis/universalis AA with the
12
248
specific Th2 antagonist dupilumab (targeting IL-4 receptor α), given for concomitant AD.47-50
249
Nevertheless, hair loss with dupilumab has also been documented.51-54 The hypothesis of Th2
250
targeting in AA patients is currently tested in a placebo-controlled trial (ClinicalTrial.gov
251
identifier: NCT03359356).
252
The immune signature of AA is complex, including dysregulations of Th1/IFNγ, Th2, IL-
253
9, PDE4, and IL-23-related cytokines.12,17,18 While JAK inhibitors are effective, the long term
254
safety is unknown.55 Furthermore, these agents cannot dissect the contribution of specific
255
immune axes to the AA phenotype, due to their wide, non-specific, down-stream suppression.
256
The strong Th2 up-regulation in AA, together with the significant associations with other atopic
257
comorbidities and particularly AD, suggest that the traditional view of AA as a primarily Th1-
258
centered disease, should be expanded. Th2-targeting agents may hold promise in AA, and the
259
relevance of this axis should be revealed through the ongoing and future therapeutic testing with
260
dupilumab and other Th2 targeting agents.
261
Our study has several limitations. The cross-sectional design does not enable to evaluate
262
a temporal relationship between AA and atopic diseases, so that causal relationship cannot be
263
drawn. Data concerning the severity of AA is not available in CHS registry, as it designed for
264
clinical purposes and not for research purposes. Another drawback of the current study is the
265
lack of direct validation of the diagnosis of AA and atopic comorbidities. Nevertheless, we used
266
stringent rules for diagnosis of AA in our study as we used only diagnoses made by
267
dermatologists. Moreover, previous studies based on the CHS registry have shown that the data
268
is of high reliability and external validity.56 A detection bias may stem from the fact that patients
269
with frequent physician contact for one condition may be more likely to have their diagnoses of
270
other conditions recorded. Unfortunately, we were not able to adjust for healthcare utilization in
13
271
the current study, and, thus, could not exclude the presence of some sort of a detection or
272
ascertainment bias.
273
In conclusion, our large-scale study revealed a significant association between AA and
274
several atopic comorbidities (table E1). Future clinical trials should ascertain whether AA can be
275
considered as part of the “atopic” umbrella. Nevertheless, physicians managing patients with AA
276
should be encouraged to evaluate these patients for the presence of atopic manifestations.
277 278
14
15 279
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Wenzel S, Castro M, Corren J, Maspero J, Wang L, Zhang B, et al. Dupilumab efficacy
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Blauvelt A, de Bruin-Weller M, Gooderham M, Cather JC, Weisman J, Pariser D, et al.
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concomitant topical corticosteroids (LIBERTY AD CHRONOS): a 1-year, randomised,
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double-blinded, placebo-controlled, phase 3 trial. Lancet 2017; 389:2287-303.
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polyps and comorbid asthma. J Allergy Clin Immunol Pract 2019.
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Inui S, Nakajima T, Toda N, Itami S. Fexofenadine hydrochloride enhances the efficacy
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of contact immunotherapy for extensive alopecia areata: Retrospective analysis of 121
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Nonomura Y, Otsuka A, Miyachi Y, Kabashima K. Case of intractable ophiasis type of alopecia areata presumably improved by fexofenadine. J Dermatol 2012; 39:1063-4.
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second-generation anti-histamine, as a supportive medication for alopecia areata. J
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Czarnowicki T, He HY, Wen HC, Hashim PW, Nia JK, Malik K, et al. Alopecia areata is
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characterized by expansion of circulating Th2/Tc2/Th22, within the skin-homing and
404
systemic T-cell populations. Allergy 2018; 73:713-23.
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46.
Song T, Pavel AB, Wen HC, Malik K, Estrada Y, Gonzalez J, et al. An integrated model
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of alopecia areata biomarkers highlights both TH1 and TH2 upregulation. J Allergy Clin
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Immunol 2018; 142:1631-4 e13.
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Sevray M, Dupre D, Misery L, Abasq-Thomas C. Hair regrowth and dissemination of
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Penzi LR, Yasuda M, Manatis-Lornell A, Hagigeorges D, Senna MM. Hair Regrowth in
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a Patient With Long-standing Alopecia Totalis and Atopic Dermatitis Treated With
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Dupilumab. JAMA Dermatol 2018; 154:1358-60.
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Dobkin H, Mullen R, Zirwas M. Alopecia Universalis and Atopic Dermatitis
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Improvement with Dupilumab: Demonstration of a Shared Pathophysiology and Clinical
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Efficacy. Skinmed 2019; 17:139-40.
419
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alopecia areata. J Am Acad Dermatol 2019. 52.
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Chung J, Slaught CL, Simpson EL. Alopecia areata in 2 patients treated with dupilumab: New onset and worsening. JAAD Case Rep 2019; 5:643-5.
53.
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Carnicle JM, Hendricks AJ, Shi VY. Reactivation of Alopecia Areata After Dupilumab Therapy for Atopic Dermatitis. Dermatitis 2019.
54.
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Maloney NJ, Worswick S, Cheng K. Development of alopecia in patients treated with dupilumab. Dermatol Ther 2019; 32:e12869.
427
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Gilhar A, Keren A, Paus R. JAK inhibitors and alopecia areata. Lancet 2019; 393:318-9.
428
56.
Birkenfeld S, Dreiher J, Weitzman D, Cohen AD. Coeliac disease associated with
429 430
psoriasis. Br J Dermatol 2009; 161:1331-4.
22 431 432
Tables Table 1- Descriptive characteristics of the study population Characteristic
Alopecia areata (n=51,561)
Controls (n=51,410)
433
Age, years Mean±SD 34.1±17.1 34.1±17.0 Median (range) 34.0 (0-99.0) 34.0 (0-99.0) Male sex, n (%) 31,085 (60.3%) 31,001 (60.3%) Ethnicity, n (%) Jews 34,800 (67.5%) 34,656 (67.4%) Arabs 16,761 (32.5%) 16,754 (32.6%) SES, n (%) Low 25,218 (48.9%) 25,179 (48.9%) Intermediate 17,396 (33.7%) 17,328 (33.7%) High 8,758 (17.0%) 8,720 (17.0%) Unknown 189 (0.4%) 183 (0.4%) Charlson comorbidity score, n (%) None (0) 42,076 (81.6%) 42,383 (82.4%) Moderate (1-2) 8,133 (15.8%) 7,673 (14.9%) Severe (≥3) 1,352 (2.6%) 1,354 (2.6%) Body mass index 25.5 ± 6.3 25.9 ± 5.6 (Kg/m2), Mean±SD Abbreviations: n, number; SD, standard deviation; BMI, body mass index; SES, socioeconomic
434
status
23 Table 2 - Demographic distribution of cases and controls with atopic comorbidities. Asthma
Atopic dermatitis
Allergic rhinitis
Allergic
(n=7,386), n (%)
(n=3,363), n (%)
(n=14,822), n (%)
conjunctivitis (n=22,199), n (%)
Character
AA
Control
AA
Control
AA
Control
AA
Control
istic
(n=51,5
(n=51,4
(n=51,5
(n=51,4
(n=51,5
(n=51,4
(n=51,5
(n=51,4
61)
10)
61)
10)
61)
10)
61)
10)
All
4,040
3,346
2,034
1,329
8,230
6,592
12,137
10,062
(n=102,97
(7.8)
(6.5)
(3.9)
(2.6)
(16.0)
(12.8)
(23.5)
(19.6)
Male
2507
2,136
1,094
664
4,763
3,768
6,719
5,445
(n=62,086)
(8.1)
(6.9)
(3.5)
(2.1)
(15.3)
(12.2)
(21.6)
(17.6)
Female
1,533
1,210
940
665
3,467
2,824
5,418
4,617
(n=40,885)
(7.5)
(5.9)
(4.6)
(3.3)
(16.9)
(13.8)
(26.5)
(22.6)
1)
Abbreviations: AA, alopecia areata; n, number. Bold: significant value
24 Table 3 - The association between alopecia areata and atopic comorbidities Disease
Asthma
AA
Controls
OR
Univariate
Male-specific
Female-specific
Adjusted OR
(n=51,561),
(n=51,410),
(95%CI)
p value
OR(95%CI)
OR(95%CI)
(95%CI)1
n (%)
n (%)
4,040 (7.8)
3,346 (6.5)
1.22 (1.17-
<0.001
1.19 (1.12-
1.28 (1.19-1.39)
1.24 (0.18-
1.28) Atopic
2,034 (3.9)
1,329 (2.6)
dermatitis Allergic
1.55 (1.44-
1.26) <0.001
1.66) 8,230 (16.0)
6,592 (12.8)
rhinitis
1.29 (1.25-
1,2137
10,062
1.27 (1.23-
conjunctivitis
(23.5)
(19.6)
1.30)
1.43 (1.29-1.58)
1.84) <0.001
1.34)
Allergic
1.67 (1.51-
1.31)
1.31 (1.25-
1.67) 1.27 (1.20-1.34)
1.37) <0.001
1.29 (1.24-
1.56 (1.45-
1.29 (1.251.34)
1.23 (1.18-1.29)
1.35)
1.27 (1.231.31)
Abbreviations: AA, alopecia areata; N, Number; OR, odds ratio; CI, confidence interval. Bold: significant value 1
-Multivariate logistic regression model adjusting for age, sex, ethnicity, socioeconomic status, and Charlson comorbidity index.
25 Table 4 - Comparison between patients with alopecia areata and atopic comorbidities relative to those with isolated alopecia areata AA w/
AA w/o
asthma
asthma
(n=4,040)
(n=47,521)
p value
AA w/ AD (n=2,034)
AA w/o
p value
AA w/
AA w/o
p value
AA w/ allergic
AA w/o
AD
allergic
allergic
conjunctivitis
allergic
(n=49,527)
rhinitis
rhinitis
(n=12,137)
conjunctivitis
(n=8,230)
(n=43,331)
p value
(n=39,424)
33.4±17.2
34.1±12.0
0.011
26.5±17.3
34.5±17.0
<0.001
37.0±16.2
34.0±17.0
<0.001
34.0±17.1
34.2±17.1
0.259
F sex, n
1,533
18,943
0.013
940 (46.2)
19,536
<0.001
894 (10.9)
19,582
<0.001
5,418 (44.6)
15,058 (38.2)
<0.001
(%)
(37.9)
(39.9)
BMI
25.4 ±5.5
25.3 ± 5.3
0.265
23.7±5.4
25.3±5.3
<0.001
25.4±5.0
25.3±5.3
0.099
25.4±5.3
25.2±5.3
<0.001
Smoking
1,437
16,489
0.249
420 (20.6)
17,506
<0.001
647 (7.9)
17,279
<0.001
3,635 (29.9)
1,4291 (36.2)
<0.001
status, n
(35.6)
(34.7)
Age at AA onset
(39.4)
(35.3)
(45.2)
(39.9)
(%)
Abbreviations: AA, alopecia areata; AD, atopic dermatitis; F, female; n, number; BMI, body mass index; w/, with; w/o, without. Bold: significant value.
26 Table 5 - The association between alopecia areata and multiple atopic comorbidities Disease
AA (n=51,561), n (%)
Controls (n=51,410), n (%)
OR (95%CI)
Univariate p value
Male-specific OR(95%CI)
Femalespecific OR(95%CI)
Adjusted OR (95%CI)1
Any atopic comorbidity
20,372 (39.5)
16,931 (32.9)
1.33 (1.30 1.37)
<0.001
1.35 (1.311.40)
1.31 (1.251.36)
1.34 (1.301.38)
≥2 concomitant atopic comorbidities
5,232 (10.1)
3,852 (7.5)
1.39 (1.341.46)
<0.001
1.40 (1.321.49)
1.39 (1.301.48)
1.40 (1.341.46)
≥3 concomitant atopic comorbidities
772 (1.5)
504 (1.0)
1.54 (1.371.72)
<0.001
1.55 (1.331.79)
1.52 (1.281.81)
1.52 (1.361.71)
Abbreviations: AA, alopecia areata; N, Number; OR, odds ratio; CI, confidence interval; Bold: significant value 1-Multivariate logistic regression model adjusting for age, sex, ethnicity, socioeconomic status, and Charlson comorbidity index.
27
Table E1- Distribution of cases and controls with atopic comorbidities stratified by age.
Asthma
Atopic dermatitis
Allergic rhinitis
Allergic conjunctivitis
(n=7,386), n (%)
(n=3,363), n (%)
(n=14,822), n (%
(n=22,199), n (%)
AA
AA
AA
Control
AA
Control
(n=51,561)
(n=51,410)
(n=51,561)
(n=51,410)
Control
Control
(n=51,561) (n=51,410) (n=51,561) (n=51,410)
Age category (years) <20 (n=22960)
967 (8.4)
848 (7.4)
932 (8.1)
695 (6.1)
1,193 (10.4)
948 (8.3)
3,168 (27.6)
2,764 (24.1)
20-39 (n=44002)
1,824 (8.3)
1,526 (6.9)
628 (2.9)
371 (1.7)
3,818 (17.3)
3,143 (14.3)
4,817 (21.9)
3,911 (17.8)
40-59 (n=27307)
877 (6.4)
649 (4.8)
375 (2.7)
200 (1.5)
2,376 (17.4)
1,842 (13.5)
3,053 (22.3)
2,435 (17.9)
≥60 (n=8702)
372 (8.5)
323 (7.5)
99 (2.3)
63 (1.5)
843 (19.3)
659 (15.2)
1,099 (25.2)
952 (22.0)
S2213-2198(20)30139-2
DOI:
https://doi.org/10.1016/j.jaip.2020.01.052
Reference:
JAIP 2682
To appear in:
The Journal of Allergy and Clinical Immunology: In Practice
Received Date: 24 October 2019 Revised Date:
3 January 2020
Accepted Date: 8 January 2020
Please cite this article as: Kridin K, Renert-Yuval Y, Guttman-Yassky E, Cohen AD, Alopecia Areata is Associated with Atopic Diathesis; Results from a Population-Based Study of 51,561 Patients The Journal of Allergy and Clinical Immunology: In Practice (2020), doi: https://doi.org/10.1016/ j.jaip.2020.01.052. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier Inc. on behalf of the American Academy of Allergy, Asthma & Immunology
1
Title: Alopecia Areata is Associated with Atopic Diathesis;
2
Results from a Population-Based Study of 51,561 Patients
3 4
Khalaf Kridin, MD, PhD,1*¶ Yael Renert-Yuval, MD,2* Emma Guttman-Yassky, MD, PhD,3**
5
Arnon D Cohen, MD, MPH, PhD4**
6 7
1
Department of Dermatology, Rambam Health Care Campus, Haifa, Israel
8
2
Laboratory for Investigative Dermatology, Rockefeller University, New York, NY, USA
9
3
Department of Dermatology and the Laboratory for Inflammatory Skin Diseases, Icahn School
10
of Medicine at Mount Sinai, New York, NY, USA
11
4
12
Gurion University of the Negev, Beer-Sheva, Israel
Siaal Research Center for Family Medicine and Primary Care, Faculty of Health Sciences, Ben-
13 14
* - Equal contribution, ** - Equal contribution
15 16
¶
17
Khalaf Kridin, MD, PhD
18
Department of Dermatology
19
Rambam Health Care Campus
20
POB 9602
21
Haifa 31096, Israel
22
Email: [email protected]
23
Telephone:+ 972-526506441
Corresponding Author:
1
24
Word count: 2208
25
Tables: 5
26
Funding: This research did not receive any specific grant from funding agencies in the public,
27
commercial, or not-for-profit sectors.
28
Conflict of interest: EGY is an employee of Mount Sinai and has received research funds
29
(grants paid to the institution) from Abbvie, Asana Biosciences, Celgene, Dermavant, DS
30
Biopharma, Galderma, Glenmark, Innovaderm, Janssen Biotech, Leo Pharma, Novan, Novartis,
31
Pfizer, Ralexar, Regeneron, and Union Therapeutics. EGY is also a consultant for Abbvie,
32
Allergan, Amgen, Asana Biosciences, Celgene, Concert, DBV Technologies, Dermira, DS
33
Biopharma, Eli Lilly, EMD Serono, Escalier, Flx Bio, Galderma, Glenmark, Kyowa Kirin, Leo
34
Pharma, Mitsubishi Tanabe, Novartis, Pfizer, Regeneron, Sanofi, and Union Therapeutics. ADC
35
received research grants from Janssen, Novartis and AbbVie, and served as a consultant, advisor
36
or speaker to AbbVie, Amgen, Boehringer Ingelheim, Dexcel pharma, Janssen, Lilly, Neopharm,
37
Novartis, Perrigo, Pfizer and Rafa. Other authors have declared that they have no conflict of
38
interest.
39 40 41
2
42
Abstract
43
Background: Evidence of Th1/interferon (IFN)γ over-activation as major pathogenic driver
44
somewhat conflicts with data supporting robust allergic background in alopecia areata (AA)
45
patients. Previous investigations of immunologic dysregulations show both Th1 and Th2-
46
related markers are over-expressed in AA. Clinical correlations in large populations may shed
47
light on the immune pathways most likely to result in the clinical phenotype of AA.
48
Objective: To investigate the atopic comorbidities among patients with AA in a large,
49
population-based study.
50
Methods: This is a cross-sectional retrospective study of AA patients and a matched
51
comparison group, analyzing the associations between AA and four atopic comorbidities:
52
asthma, atopic dermatitis (AD), allergic rhinitis, and allergic conjunctivitis. Chi-square and t-
53
tests were used for univariate analysis, and logistic regression model was used for
54
multivariate analysis. The study was performed utilizing the computerized database of Clalit
55
Health Services ensuring 4.4 million subjects.
56
Results: The study population includes 51,561 AA patients and 51,410 matched control
57
subjects. The prevalence of asthma (7.8% vs. 6.5%; OR 1.22; 95%CI 1.17-1.28, p<0.001),
58
AD (3.9% vs. 2.6%; OR 1.55; 95%CI 1.44-1.66, p<0.001), allergic rhinitis (16.0% vs. 12.8%;
59
OR 1.29; 95%CI 1.25-1.34, p<0.001), and allergic conjunctivitis (23.5% vs. 19.6%; OR 1.27;
60
95%CI 1.23-1.30, p <0.001) was significantly higher among patients with AA as compared to
61
matched control subjects. AA patients also had significantly higher probability to have more
62
than one atopic comorbidity, with increasing OR as the number of concomitant atopic
63
conditions increases.
3
64
Conclusion: Our analysis supports the previous literature and provides strong generalizability
65
of significant atopy in AA patients, suggesting Th2 pathogenicity in AA, and challenging the
66
traditional view of AA as a single axis, Th1-centered disease.
67
4
68 69 70 71 72 73 74 75 76 77
Highlights box - no longer than 35 words in each • • •
What is already known about this topic? There is conflicting evidence for both Th1/interferon (IFN)γ and Th2-related markers as drivers of the inflammatory process of alopecia areata (AA). What is already known about this topic? AA patients had significant atopic associations as compared to a matched control group, in line with previous, smaller-scale publications. These findings lend weight to the concept of Th2-skewing in AA. What is already known about this topic? Our study reinforces a rationale for Th2targeting approaches in patients with AA.
78
Key words: Alopecia areata, population based, atopic dermatitis, asthma, allergic rhinitis,
79
allergic conjunctivitis, comorbidities, atopy, big data.
80 81
Abbreviations used:
82
AA: Alopecia areata
83
AD: Atopic dermatitis
84
CHS: Clalit Health Services
85
CI: Confidence interval
86
OR: Odds ratio
87
5
88
Introduction
89
Alopecia areata (AA) is a common dermatologic disease, affecting up to 2% of the population,
90
and is characterized by non-scarring hair loss.1-3 Clinical presentations range from patchy,
91
circumscribed hair loss to alopecia totalis or universalis (complete loss of scalp hair or scalp and
92
body hair, respectively).3 Despite significant emotional and psychosocial distress for patients and
93
their families,4 AA has no definitive, safe, and effective treatment,5-8 and the incomplete
94
understanding of AA pathogenesis hinders further therapeutic developments.9,10 While consensus
95
exists for the hair follicle immune privilege disruption as a trigger of hair follicle immune
96
attack,11 the immune pathways driving the inflammatory response resulting in hair loss are not
97
yet fully elucidated. Traditionally, Th1/interferon/IFNγ-related cytokines and chemokines have
98
been viewed as chief players in AA initiation and maintenance, as supported by animal
99
models.12,13 The newly introduced Janus kinase/JAK inhibitors were also shown to downregulate
100
Th1/IFNγ and associated markers, along with other immune axes, such as Th2 coupled with up-
101
regulations of hair keratins.14-16 Moreover, dysregulations of Th1/IFNγ, Th2, IL-9, PDE4, and
102
Th17/IL-23 were found in several human and in mouse AA studies.12,17,18 Increasing evidence
103
for a possible role of Th2 immune pathway in AA is supported by the high levels of Th2- related
104
cytokines (e.g. IL-4, IL-5, IL-10) in skin and serum of AA patients, as well as findings of
105
eosinophilia and elevated IgE levels in blood from AA patients.17,19-21 Moreover, genetic studies
106
have identified polymorphisms in filaggrin, IL-4, and IL-13 (key players of the Th2 pathway) in
107
AA patients, and associated filaggrin mutations with AA severity.19,22,23
108
Few preliminary epidemiological studies and meta-analyses have shown a higher
109
prevalence of atopic diseases, such as atopic dermatitis (AD), asthma, and allergic rhinitis
110
(commonly driven by Th2-skewing) in patients with AA, hinting towards a shared
6
111
immunological background in these conditions.3,24-28 Last, the therapeutic armamentarium
112
available for patients with atopic conditions, including AD, is rapidly expanding,29 and it is thus
113
important to further understand the associations between these conditions and AA.
114
We investigated the association between AA and Th2-related diseases in a uniquely large
115
and detailed database from Israel, in which patients have long-term follow-up of various health-
116
related systems. We opted to complement previous data suggesting Th2 skewing in AA patients.
117
To the best of our knowledge, this is the largest population-based study investigating the atopic
118
comorbidities of AA patients, encompassing more than 4.4 million patients.
119 120
Methods
121
Study design and setting
122
The current study was designed as a cross-sectional retrospective study utilizing
123
information from the Clalit Health Services (CHS) database. CHS is the largest health
124
maintenance organization in Israel, serving a population of approximately 4,400,000 as for 2017.
125
CHS has a comprehensive computerized database with incessant real-time input from medical,
126
administrative, and pharmaceutical computerized operating systems that enables data collection
127
for epidemiological studies. The validity of diagnoses in this dataset, which are based on reports
128
from both hospital and primary care physicians and specialists, was proven highly reliabile9. A
129
chronic disease register is gathered from these data sources and continuously updated and
130
validated through algorithmic checks9. The current study was approved by the institutional
131
ethical board of Ben-Gurion University and CHS.
132
Study population and covariates
7
133
All medical records of CHS enrollees were screened for the diagnosis of AA, and data on
134
prevalent cases of AA was retrieved. The diagnosis of AA was based on the documentation of an
135
AA-specific diagnostic code registered by a board-certified dermatologist. A comparison group
136
of individuals without AA was selected through 1:1 matching based on age, sex, ethnicity, and
137
primary care practice. The control group was randomly selected from the list of CHS enrollees'
138
frequency-matched to cases, excluding case patients with AA. Age matching was grounded on
139
the exact year of birth (1-year strata).
140
Other covariates in the analysis included: comorbid conditions as determined using
141
Charlson comorbidity index,10 a weighted index used to categorize the degree of comorbidity of
142
a patient by taking into account the number and seriousness of comorbid conditions. This
143
validated method has been shown to be a robust predictor of mortality and it correlates positively
144
with a fatal outcome.10 Socioeconomic status was defined according to the poverty index of the
145
patient's residence area as defined during the 2008 National Census. The population was divided
146
into 3 categories according to their poverty index (low, intermediate, and high)11. Data on
147
ethnicity was based on the address of the patient’s primary care clinic. The vast majority of the
148
Arab population in Israel resides in highly homogenous Arab towns and villages. Patients
149
affiliated to healthcare facilities in these towns are designated as belonging to the “Arab Sector”.
150
Thus, primary care clinic location represents a relatively precise measure of the ethnicity of
151
patients in Israel.
152
Statistical analysis
153
The distribution of sociodemographic and clinical features was compared between case
154
and control subjects using chi-square test for sex and socioeconomic status, and t-test for age.
155
Conditional logistic regression was then used to calculate adjusted odds ratio (OR), and 95%
8
156
confidence interval (CI), to compare cases and controls with respect to the presence of atopic
157
comorbidities. All statistical analyses were performed using SPSS software, version 23 (SPSS,
158
Chicago, IL, USA).
159 160
Results
161
Our study population comprised of 51,561 patients with AA and 51,410 age- and sex-
162
matched control subjects. The mean age (±standard deviation/SD) of patients with AA was
163
34.1±17.1, which is identical to that of control subjects at the date of enrollment. Overall, 20,476
164
(39.7%) of AA patients were females and a similar proportion was documented among controls.
165
No significant differences in ethnic background and socioeconomic status were noted between
166
the two groups. Comorbidity rates, measured by the Charlson comorbidity index, were
167
comparable between the two groups, with 1,352 (2.6%) AA patients and 1,354 (2.6%) control
168
subjects experiencing severe comorbidities. The mean body mass index (BMI) was lower among
169
patients with AA (Table 1).
170
We evaluated the presence of four atopic conditions (AD, asthma, allergic rhinitis, and
171
allergic conjunctivitis) among AA patients and control groups. Table 2 demonstrates the
172
proportions of AA patients and controls with atopic comorbidities stratified by sex and age
173
category. The prevalence of asthma (7.8% vs. 6.5%; p<0.001), AD (3.9% vs. 2.6%; p<0.001),
174
allergic rhinitis (16.0% vs. 12.8%; p<0.001), and allergic conjunctivitis (23.5% vs. 19.6%;
175
p<0.001) was significantly higher among patients with AA as compared to matched control
176
subjects. In both AA and controls, the highest prevalence of both AD and Allergic conjunctivitis
177
was reported in patients younger than 20 years of age. Table 3 presents the results of univariate
178
and logistic regression models, and summarizes ORs for atopic conditions in patients with AA
9
179
and controls across the entire study sample. Among included atopic diseases, AD demonstrated
180
the strongest association with AA (OR, 1.55; 95% CI, 1.44-1.66). A milder, but still statistically
181
significant increase, was observed in the odds of asthma (OR, 1.22; 95% CI, 1.17–1.28), allergic
182
rhinitis (OR, 1.29; 95% CI, 1.25–1.34), and allerigc conjuncitivits (OR, 1.27; 95% CI, 1.23–
183
1.30) among patients with AA relative to control subjects. In a multivariate logistic regression
184
model, adjustment for age, sex, ethnicity, socioeconomic status, and comorbidities did not
185
interfere with any of the aforementioned significant associations (Table 3).
186
We compared the characteristics of patients with AA presenting with comorbid atopic
187
diseases relative to patients with isolated AA (Table 4). Patients with comorbid asthma and AD
188
presented with their AA at a significantly earlier age, whereas patients with comorbid allergic
189
rhinitis developed AA at an older age. An overwhelming male preponderance was observed
190
among patients with AA and comorbid allergic rhinitis, whereas a slighter female predominance
191
emerged among patients with AA and comorbid AD and allergic conjunctivitis. Notably, patients
192
with AA and comorbid allergic rhinitis, AD and, to a lesser extent, allergic conjunctivitis were
193
less frequently exposed to cigarette smoking (Table 4).
194
Lastly, we investigated the association between having one or more atopic comorbidities
195
in AA patients as compared to controls. The prevalence of at least a single atopic comorbidity
196
was greater among patients with AA as compared to control subjects (39.5% vs. 32.9%,
197
respectively; OR, 1.33; 95% CI, 1.30–1.37; p<0.001). The prevalence of two or more (≥2)
198
concomitant atopic conditions was significantly higher among AA patients than controls (10.1%
199
vs. 7.5%, respectively; OR, 1.39; 95% CI, 1.34–1.46; p<0.001). When the probability of having
200
three or more (≥3) concomitant atopic conditions was compared, even a more robust association
201
was revealed (1.5% vs. 1.0%, respectively; OR, 1.54; 95% CI, 1.37–1.72; p<0.001). All the
10
202
aforementioned associations were robust to a multivariate analysis adjusting for age, sex,
203
ethnicity, socioeconomic status, and comorbidities (Table 5).
204 205 206
Discussion
207
Various comorbidities been reported in patients with AA, including psychological,
208
autoimmune, and atopic diseases.24-26,30,31 However, the association between AA and atopic
209
diseases has been evaluated in small cohorts.24-28 In the current population-based study, we
210
investigated the prevalence of atopic comorbidities in 51,561 patients with AA and 51,410
211
matched controls, to better characterize these associations. Of all four atopic comorbidities
212
included in this study, the most robust association of AA was with concomitant AD. The most
213
prevalent atopic disease in the entire cohort was allergic conjunctivitis, similar to previous
214
publications,32 and AA was also significantly associated with this condition, although to a lesser
215
extent in comparison with.
216
AA patients with concomitant AD and asthma were associated with an earlier onset of
217
AA, similar to prior reports.25,26 This together with the fact that early AA onset is recognized as a
218
risk factor for more recalcitrant disease,33 potentially support a shared underlying immune
219
dysregulation in the disease burden of AA and the atopic comorbidities. Notably, significanly
220
more AA patients with concomitant AD, allergic rhinitis, and allergic conjuctivitis were non-
221
smokers, theoratically hinting towards an anti-inflammatory, nicotine-mediated effect, as seen in
222
ulcerative colitis and pemphigus.34,35 Despite these findings, because the overall hazards of
223
smoking are well known, and lung cancer-related mortatility is particularly higher in AA
224
patients,36 smoking cessation recommendations should still be stressed in AA patients.
11
225
Since atopic diseases are often manifested concomitantly, a phenomenon referred to as
226
the “atopic march” in the pediatric population,37 we evaluated the OR of patients with AA to
227
have several atopic comorbidities in comparison to patients without AA. We found that patients
228
with AA are more likely to suffer from concomitant atopic comorbidities with increasing OR as
229
the number of concomitant atopic conditions increases.
230
The mechanisms leading to the clinical manifestations of AA are still elusive, although
231
recent research efforts portray an immune-mediated disease with variable activation of polar
232
cytokine axes, including both Th1 and Th2.17 Th2 upregulations can be anticipated in patients
233
with concomitant atopic diseases, specifically AD, asthma, and allergic rhinitis patients, in which
234
Th2 pathway pathogenicity has been recently demonstrated by the efficacy of Th2-targeting
235
agents.38-40 Of note, a large study evaluating scalp of AA patients with and without AD, did not
236
show differences in Th2 activation in AA patients, regardless of their atopic status.17
237
Furthermore, in a large genome-wide association study, IL-13 has been the strongest association
238
in AA patients, regardless of concomitant AD.22 The atopic associations in AA patients have led
239
to testing of anti-histamines with beneficial effects in some AA patients, leading to several
240
reports advocating for concomitant antihistamine use together with other treatments in AA
241
patients.41-43
242
AA management presents significant unmet needs, particularly in patients with moderate
243
to severe hair loss, where intra-lesional and conventional therapeutics have limited applicability
244
and efficacy.9,10,44 Due to significant associations between atopic diseases and AA, as well as the
245
increasing evidence of up-regulations of Th2-related products in AA skin and blood,17,19-21,45,46 a
246
rationale for possible anti-Th2 approaches emerges in AA patients. This is also supported by few
247
case reports of significant hair regrowth in AA patients with totalis/universalis AA with the
12
248
specific Th2 antagonist dupilumab (targeting IL-4 receptor α), given for concomitant AD.47-50
249
Nevertheless, hair loss with dupilumab has also been documented.51-54 The hypothesis of Th2
250
targeting in AA patients is currently tested in a placebo-controlled trial (ClinicalTrial.gov
251
identifier: NCT03359356).
252
The immune signature of AA is complex, including dysregulations of Th1/IFNγ, Th2, IL-
253
9, PDE4, and IL-23-related cytokines.12,17,18 While JAK inhibitors are effective, the long term
254
safety is unknown.55 Furthermore, these agents cannot dissect the contribution of specific
255
immune axes to the AA phenotype, due to their wide, non-specific, down-stream suppression.
256
The strong Th2 up-regulation in AA, together with the significant associations with other atopic
257
comorbidities and particularly AD, suggest that the traditional view of AA as a primarily Th1-
258
centered disease, should be expanded. Th2-targeting agents may hold promise in AA, and the
259
relevance of this axis should be revealed through the ongoing and future therapeutic testing with
260
dupilumab and other Th2 targeting agents.
261
Our study has several limitations. The cross-sectional design does not enable to evaluate
262
a temporal relationship between AA and atopic diseases, so that causal relationship cannot be
263
drawn. Data concerning the severity of AA is not available in CHS registry, as it designed for
264
clinical purposes and not for research purposes. Another drawback of the current study is the
265
lack of direct validation of the diagnosis of AA and atopic comorbidities. Nevertheless, we used
266
stringent rules for diagnosis of AA in our study as we used only diagnoses made by
267
dermatologists. Moreover, previous studies based on the CHS registry have shown that the data
268
is of high reliability and external validity.56 A detection bias may stem from the fact that patients
269
with frequent physician contact for one condition may be more likely to have their diagnoses of
270
other conditions recorded. Unfortunately, we were not able to adjust for healthcare utilization in
13
271
the current study, and, thus, could not exclude the presence of some sort of a detection or
272
ascertainment bias.
273
In conclusion, our large-scale study revealed a significant association between AA and
274
several atopic comorbidities (table E1). Future clinical trials should ascertain whether AA can be
275
considered as part of the “atopic” umbrella. Nevertheless, physicians managing patients with AA
276
should be encouraged to evaluate these patients for the presence of atopic manifestations.
277 278
14
15 279
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280
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Tables Table 1- Descriptive characteristics of the study population Characteristic
Alopecia areata (n=51,561)
Controls (n=51,410)
433
Age, years Mean±SD 34.1±17.1 34.1±17.0 Median (range) 34.0 (0-99.0) 34.0 (0-99.0) Male sex, n (%) 31,085 (60.3%) 31,001 (60.3%) Ethnicity, n (%) Jews 34,800 (67.5%) 34,656 (67.4%) Arabs 16,761 (32.5%) 16,754 (32.6%) SES, n (%) Low 25,218 (48.9%) 25,179 (48.9%) Intermediate 17,396 (33.7%) 17,328 (33.7%) High 8,758 (17.0%) 8,720 (17.0%) Unknown 189 (0.4%) 183 (0.4%) Charlson comorbidity score, n (%) None (0) 42,076 (81.6%) 42,383 (82.4%) Moderate (1-2) 8,133 (15.8%) 7,673 (14.9%) Severe (≥3) 1,352 (2.6%) 1,354 (2.6%) Body mass index 25.5 ± 6.3 25.9 ± 5.6 (Kg/m2), Mean±SD Abbreviations: n, number; SD, standard deviation; BMI, body mass index; SES, socioeconomic
434
status
23 Table 2 - Demographic distribution of cases and controls with atopic comorbidities. Asthma
Atopic dermatitis
Allergic rhinitis
Allergic
(n=7,386), n (%)
(n=3,363), n (%)
(n=14,822), n (%)
conjunctivitis (n=22,199), n (%)
Character
AA
Control
AA
Control
AA
Control
AA
Control
istic
(n=51,5
(n=51,4
(n=51,5
(n=51,4
(n=51,5
(n=51,4
(n=51,5
(n=51,4
61)
10)
61)
10)
61)
10)
61)
10)
All
4,040
3,346
2,034
1,329
8,230
6,592
12,137
10,062
(n=102,97
(7.8)
(6.5)
(3.9)
(2.6)
(16.0)
(12.8)
(23.5)
(19.6)
Male
2507
2,136
1,094
664
4,763
3,768
6,719
5,445
(n=62,086)
(8.1)
(6.9)
(3.5)
(2.1)
(15.3)
(12.2)
(21.6)
(17.6)
Female
1,533
1,210
940
665
3,467
2,824
5,418
4,617
(n=40,885)
(7.5)
(5.9)
(4.6)
(3.3)
(16.9)
(13.8)
(26.5)
(22.6)
1)
Abbreviations: AA, alopecia areata; n, number. Bold: significant value
24 Table 3 - The association between alopecia areata and atopic comorbidities Disease
Asthma
AA
Controls
OR
Univariate
Male-specific
Female-specific
Adjusted OR
(n=51,561),
(n=51,410),
(95%CI)
p value
OR(95%CI)
OR(95%CI)
(95%CI)1
n (%)
n (%)
4,040 (7.8)
3,346 (6.5)
1.22 (1.17-
<0.001
1.19 (1.12-
1.28 (1.19-1.39)
1.24 (0.18-
1.28) Atopic
2,034 (3.9)
1,329 (2.6)
dermatitis Allergic
1.55 (1.44-
1.26) <0.001
1.66) 8,230 (16.0)
6,592 (12.8)
rhinitis
1.29 (1.25-
1,2137
10,062
1.27 (1.23-
conjunctivitis
(23.5)
(19.6)
1.30)
1.43 (1.29-1.58)
1.84) <0.001
1.34)
Allergic
1.67 (1.51-
1.31)
1.31 (1.25-
1.67) 1.27 (1.20-1.34)
1.37) <0.001
1.29 (1.24-
1.56 (1.45-
1.29 (1.251.34)
1.23 (1.18-1.29)
1.35)
1.27 (1.231.31)
Abbreviations: AA, alopecia areata; N, Number; OR, odds ratio; CI, confidence interval. Bold: significant value 1
-Multivariate logistic regression model adjusting for age, sex, ethnicity, socioeconomic status, and Charlson comorbidity index.
25 Table 4 - Comparison between patients with alopecia areata and atopic comorbidities relative to those with isolated alopecia areata AA w/
AA w/o
asthma
asthma
(n=4,040)
(n=47,521)
p value
AA w/ AD (n=2,034)
AA w/o
p value
AA w/
AA w/o
p value
AA w/ allergic
AA w/o
AD
allergic
allergic
conjunctivitis
allergic
(n=49,527)
rhinitis
rhinitis
(n=12,137)
conjunctivitis
(n=8,230)
(n=43,331)
p value
(n=39,424)
33.4±17.2
34.1±12.0
0.011
26.5±17.3
34.5±17.0
<0.001
37.0±16.2
34.0±17.0
<0.001
34.0±17.1
34.2±17.1
0.259
F sex, n
1,533
18,943
0.013
940 (46.2)
19,536
<0.001
894 (10.9)
19,582
<0.001
5,418 (44.6)
15,058 (38.2)
<0.001
(%)
(37.9)
(39.9)
BMI
25.4 ±5.5
25.3 ± 5.3
0.265
23.7±5.4
25.3±5.3
<0.001
25.4±5.0
25.3±5.3
0.099
25.4±5.3
25.2±5.3
<0.001
Smoking
1,437
16,489
0.249
420 (20.6)
17,506
<0.001
647 (7.9)
17,279
<0.001
3,635 (29.9)
1,4291 (36.2)
<0.001
status, n
(35.6)
(34.7)
Age at AA onset
(39.4)
(35.3)
(45.2)
(39.9)
(%)
Abbreviations: AA, alopecia areata; AD, atopic dermatitis; F, female; n, number; BMI, body mass index; w/, with; w/o, without. Bold: significant value.
26 Table 5 - The association between alopecia areata and multiple atopic comorbidities Disease
AA (n=51,561), n (%)
Controls (n=51,410), n (%)
OR (95%CI)
Univariate p value
Male-specific OR(95%CI)
Femalespecific OR(95%CI)
Adjusted OR (95%CI)1
Any atopic comorbidity
20,372 (39.5)
16,931 (32.9)
1.33 (1.30 1.37)
<0.001
1.35 (1.311.40)
1.31 (1.251.36)
1.34 (1.301.38)
≥2 concomitant atopic comorbidities
5,232 (10.1)
3,852 (7.5)
1.39 (1.341.46)
<0.001
1.40 (1.321.49)
1.39 (1.301.48)
1.40 (1.341.46)
≥3 concomitant atopic comorbidities
772 (1.5)
504 (1.0)
1.54 (1.371.72)
<0.001
1.55 (1.331.79)
1.52 (1.281.81)
1.52 (1.361.71)
Abbreviations: AA, alopecia areata; N, Number; OR, odds ratio; CI, confidence interval; Bold: significant value 1-Multivariate logistic regression model adjusting for age, sex, ethnicity, socioeconomic status, and Charlson comorbidity index.
27
Table E1- Distribution of cases and controls with atopic comorbidities stratified by age.
Asthma
Atopic dermatitis
Allergic rhinitis
Allergic conjunctivitis
(n=7,386), n (%)
(n=3,363), n (%)
(n=14,822), n (%
(n=22,199), n (%)
AA
AA
AA
Control
AA
Control
(n=51,561)
(n=51,410)
(n=51,561)
(n=51,410)
Control
Control
(n=51,561) (n=51,410) (n=51,561) (n=51,410)
Age category (years) <20 (n=22960)
967 (8.4)
848 (7.4)
932 (8.1)
695 (6.1)
1,193 (10.4)
948 (8.3)
3,168 (27.6)
2,764 (24.1)
20-39 (n=44002)
1,824 (8.3)
1,526 (6.9)
628 (2.9)
371 (1.7)
3,818 (17.3)
3,143 (14.3)
4,817 (21.9)
3,911 (17.8)
40-59 (n=27307)
877 (6.4)
649 (4.8)
375 (2.7)
200 (1.5)
2,376 (17.4)
1,842 (13.5)
3,053 (22.3)
2,435 (17.9)
≥60 (n=8702)
372 (8.5)
323 (7.5)
99 (2.3)
63 (1.5)
843 (19.3)
659 (15.2)
1,099 (25.2)
952 (22.0)